Smart City Gnosys

Smart city article details

Title	Energy Analysis-Based Cyber Attack Detection By Iot With Artificial Intelligence In A Sustainable Smart City
ID_Doc	23130
Authors	Prabakar D.; Sundarrajan M.; Manikandan R.; Jhanjhi N.Z.; Masud M.; Alqhatani A.
Year	2023
Published	Sustainability (Switzerland), 15, 7
DOI	http://dx.doi.org/10.3390/su15076031
Abstract	Cybersecurity continues to be a major issue for all industries engaged in digital activity given the cyclical surge in security incidents. Since more Internet of Things (IoT) devices are being used in homes, offices, transportation, healthcare, and other venues, malicious attacks are happening more frequently. Since distance between IoT as well as fog devices is closer than distance between IoT devices as well as the cloud, attacks can be quickly detected by integrating fog computing into IoT. Due to the vast amount of data produced by IoT devices, ML is commonly employed for attack detection. This research proposes novel technique in cybersecurity-based network traffic analysis and malicious attack detection using IoT artificial intelligence techniques for a sustainable smart city. A traffic analysis has been carried out using a kernel quadratic vector discriminant machine which enhances the data transmission by reducing network traffic. This enhances energy efficiency with reduced traffic. Then, the malicious attack detection is carried out using adversarial Bayesian belief networks. The experimental analysis has been carried out in terms of throughput, data traffic analysis, end-end delay, packet delivery ratio, energy efficiency, and QoS. The proposed technique attained a throughput of 98%, data traffic analysis of 74%, end-end delay of 45%, packet delivery ratio of 92%, energy efficiency of 92%, and QoS of 79%. © 2023 by the authors.
Author Keywords	artificial intelligence; cyber-attack; IoT devices; malicious attack detection; network traffic analysis; security; sustainable smart city

Similar Articles

Id	Similarity	Authors	Title	Published
17576	0.901	Nirosha V.; Hemamalini V.	Ddos Attack Detection System For Iot Enabled Smart City Applications With Correlation Analysis	2024 4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024 (2024)
58001	0.896	Rangelov D.; Lämmel P.; Brunzel L.; Borgert S.; Darius P.; Tcholtchev N.; Boerger M.	Towards An Integrated Methodology And Toolchain For Machine Learning-Based Intrusion Detection In Urban Iot Networks And Platforms	Future Internet, 15, 3 (2023)
6993	0.892	Alhamdi M.J.M.; Lopez-Guede J.M.; AlQaryouti J.; Rahebi J.; Zulueta E.; Fernandez-Gamiz U.	Ai-Based Malware Detection In Iot Networks Within Smart Cities: A Survey	Computer Communications, 233 (2025)
6153	0.887	Alrashdi I.; Alqazzaz A.; Aloufi E.; Alharthi R.; Zohdy M.; Ming H.	Ad-Iot: Anomaly Detection Of Iot Cyberattacks In Smart City Using Machine Learning	2019 IEEE 9th Annual Computing and Communication Workshop and Conference, CCWC 2019 (2019)
14401	0.887	Gore S.; Mahankale N.; Gore S.; Kadu S.; Belhe S.A.	Cloud Computing For Effective Cyber Security Attack Detection In Smart Cities	2023 4th IEEE Global Conference for Advancement in Technology, GCAT 2023 (2023)
18301	0.882	Muna R.K.; Hossain M.I.; Alam M.G.R.; Hassan M.M.; Ianni M.; Fortino G.	Demystifying Machine Learning Models Of Massive Iot Attack Detection With Explainable Ai For Sustainable And Secure Future Smart Cities	Internet of Things (Netherlands), 24 (2023)
7586	0.882	Al Dawi A.; Tezel N.S.; Rahebi J.; Akbas A.	An Approach To Botnet Attacks In The Fog Computing Layer And Apache Spark For Smart Cities	Journal of Supercomputing, 81, 4 (2025)
9232	0.882	Zhang J.	Analysis Of Network Attack Detection Based On Internet Of Things Network Traffic	Lecture Notes on Data Engineering and Communications Technologies, 155 (2023)
19430	0.88	Alhanaya M.; Al-Shqeerat K.	Developing An Integrated Framework For Securing Internet Of Things Traffic In Smart Cities Using Machine Learning Techniques	Applied Sciences (Switzerland), 13, 16 (2023)
41565	0.88	Zhukabayeva T.; Ahmad Z.; Adamova A.; Karabayev N.; Mardenov Y.; Satybaldina D.	Penetration Testing And Machine Learning-Driven Cybersecurity Framework For Iot And Smart City Wireless Networks	IEEE Access, 13 (2025)